Abstract: A method, sensor, and non-transitory computer-readable storage medium are provided for estimating actual amplitudes of a waveform. A machine learning model may be trained for an embedded system of a first three-axes sensor having a limited range to estimate the actual amplitudes of a waveform that saturates the first three-axes sensor in a direction of one of the three axes. The embedded system acquires a second waveform during use of a tool including the first three-axes sensor. The second waveform that occurs after a second waveform producing event is isolated. The embedded system extracts a multi-dimensional feature from the isolated second waveform and estimates, using the machine learning model, the actual amplitudes of the second waveform based on the extracted multi-dimensional feature.

Abstract: The disclosure relates to a method and system for downhole processing of data, such as images, including using a set of downhole sensors to measure parameters relative to the borehole at a plurality of depths and azimuths and detecting predetermined features of the borehole, using a downhole processor, with a trained machine-learning model and extracting characterization data, characterizing the shape and position of the predetermined features that are transmitted to the surface. It also provides a method and system for providing an image of a geological formation at the surface including transmitting a first dataset to the surface that will be used for reconstructing an image at the surface, downhole processing of a second dataset to detect predetermined features and extract characterization data that are transmitted at the surface and displaying a combined image comprising the predetermined features overlaid on the first image.

Abstract: The disclosure relates to a method and system for downhole processing of data, such as images, including using a set of downhole sensors to measure parameters relative to the borehole at a plurality of depths and azimuths and detecting predetermined features of the borehole, using a downhole processor, with a trained machine-learning model and extracting characterization data, characterizing the shape and position of the predetermined features that are transmitted to the surface. It also provides a method and system for providing an image of a geological formation at the surface including transmitting a first dataset to the surface that will be used for reconstructing an image at the surface, downhole processing of a second dataset to detect predetermined features and extract characterization data that are transmitted at the surface and displaying a combined image comprising the predetermined features overlaid on the first image.